Navigating through a large Web site can be a frustratingexercise. Many sites employ Site Maps to help visitorsunderstand the overall structure of the site. However, bytheir very nature, unpersonalized Site Maps show most visitorslarge amounts of irrelevant content. We propose techniquesbased on Web usage mining to deliver PersonalizedSite Maps that are specialized to the interests of each individualvisitor. The key challenge is to resolve the tension betweensimplicity (showing just relevant content), and comprehensibility(showing sufficient context so that the visitorscan understand how the content is related to the overallstructure of the site). We develop two baseline algorithms(one that displays just shortest paths, and one that minesthe server log for popular paths), and compare them to anovel approach that mines the server log for popular pathfragments that can be dynamically assembled to reconstructpopular paths. Our experiments with two large Web sitesconfirm that the mined path fragments provide much bettercoverage of visitors sessions than the baseline approach ofmining entire paths.
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